Abstract
The rapid integration of artificial intelligence (AI) into global healthcare systems has led to significant improvements in diagnostic accuracy, administrative efficiency, and personalised medical care. However, it has also introduced new challenges relating to employment displacement, workforce restructuring, and digital competency gaps. This study provides a comprehensive empirical assessment of AI’s disruptive force in the global healthcare labour market using secondary data and systematic content analysis of peerreviewed articles, institutional reports, and industry publications. Findings reveal that while AI automates routine administrative and diagnostic tasks and poses risks to lower-skill employment categories, it simultaneously creates new professional roles in digital health governance, biomedical data science, algorithmic auditing, and AI system management. The impact of AI adoption varies significantly by region: developed nations experience workforce transformation and job reallocation, while developing countries face constrained adoption due to limited infrastructure and digital skills. The study concludes that AI in healthcare is driving a shift from task-based human labour to hybrid, human–machine collaboration systems rather than complete professional replacement. To mitigate inequality and labour displacement risks, healthcare systems require proactive institutional policies, investment in workforce training, and robust ethical governance frameworks. The study contributes to the global debate on AI and workforce sustainability by offering evidence-based insights for policymakers, healthcare managers, and researchers.